The predicted models of anti-colon cancer and anti-hepatoma activities of substituted 4-anilino coumarin derivatives using quantitative structure-activity relationship (QSAR)

Objectives: The objective of this work was to predict anti-colon and anti-hepatoma cancer activity of newly designed substituted 4-anilino coumarin derivatives using quantitative structure-activity relationship (QSAR). Methods: The optimization of the derivatives including molecular and electronic properties data to generate the QSAR were resulted from H-GGA DFT/BPV86 method calculation combined with Hartree-Fock 6-31G basis set. The QSAR models were delivered in multiple linear regression (MLR) and the drug design was accomplished by considering the descriptors constructing the best QSAR models for each biological activity. Results: This research accomplished two best validated QSAR models for predicting anti-colon cancer and anti-hepatoma activities of substituted 4-anilino coumarin derivatives. There were 17 of newly designed substituted 4-anilino coumarin derivatives which their anticancer activity (Log IC50) were predicted using our both QSAR models. The QSAR predictions inform that the compound 25 and compound 19 have the best predicted anti-colon cancer and anti-hepatoma activities, respectively. Conclusion: The results revealed that this approach can be used to assist in the action of anticancer drug discovery. Moreover, the retrosynthesis analysis of both compounds are also explained in a logic reverse of organic synthetic steps through Knoevenagel and Perkin reactions. (C) 2022 The Author(s). Published by Elsevier B.V. on behalf of King Saud University.

Automated summary

This study aimed to predict the anti-colon and anti-hepatoma cancer activity of newly designed substituted 4-anilino coumarin derivatives using quantitative structure-activity relationship (QSAR). QSAR models were generated by optimizing the molecular and electronic properties data through H-GGA DFT/BPV86 method calculation. Two validated QSAR models were obtained, which successfully predicted the anticancer activity of 17 newly designed derivatives.